Many types of devices today include a digital camera that can be used to capture digital photos, such as with a mobile phone, tablet device, a digital camera device, and other electronic media devices. The accessibility and ease of use of the many types of devices that include a digital camera makes it quite easy for most anyone to take photos. Many users also want to enhance their photos, such as by cropping them to improve the visual composition and quality of the photos, or for a different aspect ratio (landscape, panoramic, etc.). A digital image, such as a photo, can be cropped to improve the composition by removing unnecessary or distracting objects from the image, while also shifting the subject focus of the image. Although there are general rules for image composition defined by expert photographers, such as the rule-of-thirds for image cropping, the composition styles and preferences can vary from one user to the next.
Due to the many varying composition styles and preferences, conventional cropping techniques include manually designing cropping rules which can involve tedious parameter adjustments for cropping by matching the hand-crafted rules. Currently, learning systems, or data-driven methods, only model composition changes before and after cropping while the composition rules are manually designed. The limitations of other techniques result in limited features of an image being determined, such as with estimation techniques used to determine the most prominent or noticeable objects or regions of an image. Other features of the image may then be removed when the image is cropped, which does not take into account the overall composition of the image and can result in a poor visual image.